Apify Store Scraper: Market Intelligence on Every Public Actor in 2026

There are thousands of public Actors on the Apify Store, and if you build or buy scrapers, the store itself is a dataset worth having: who charges what, which tools actually get used, and whose runs quietly fail. I wanted that as rows, not browsing. The Apify Store API sweeps every public Actor into flat JSON with pricing, usage trends, and reliability stats.

Disclosure: the Apify links in this post are affiliate links. If you run the Actor, I may earn a referral commission at no extra cost to you.

Doesn't Apify already have an API for this?

Partly, and credit where due: Apify's platform API is excellent for running Actors and lists basic store info. What it does not hand you is the commercial layer as one dataset: 30-day run outcomes split into succeeded, failed, aborted, and timed out, success rates, user trends over 7, 30, and 90 days, per-event pricing detail, and optional README plus input-schema enrichment, one flat row per Actor. Assembling that from public listing pages is exactly the tedious join this Actor does for you, with no platform key or subscription required.

What the Apify Store API returns

The Apify Store API returns one flat JSON row per public Actor with identity, usage, reliability, demand, and pricing fields ready for a spreadsheet or database.

Field	Example	Notes
name / username	instagram-scraper / apify	With title, url, categories
totalUsers	512340	Plus monthlyUsers and 7, 30, 90-day trends
successRate30Days	96.0	With full run-outcome breakdowns
reviewRating	4.6	And reviewCount, bookmarkCount
pricingModel	PRICE_PER_DATASET_ITEM	With pricePerUnitUsd and pricing events
readme	full text	Optional, via includeDetails

Filter by search, category, pricingModel, or username, or leave filters empty and sweep the whole store.

Who this is for

Actor developers scoping a niche before building, which is how I use it: is the category crowded, what does the incumbent charge, does it actually succeed. Developers choosing a scraper to depend on, where successRate30Days beats marketing copy. And analysts studying the web-scraping market with actual usage numbers.

The manual way, and where it breaks

You can research the store by clicking through listings and noting stats in a sheet. It works for five Actors. At fifty, the numbers you copied first are stale, the pricing models refuse to compare cleanly, and you have no reliability data at all unless you check each card again tomorrow. Store pages are built for browsing; questions like "every LinkedIn scraper sorted by 30-day success rate" need a dataset.

The faster way: run the Apify Store scraper

Apify Console

1. Open the Apify Store API and click Try for free.
2. Set a search term or category, or leave both empty for a full sweep, and cap with maxItems.
3. Run it and export the rows as JSON, CSV, or Excel.

REST

curl -X POST "https://api.apify.com/v2/acts/johnvc~store-actor-intelligence-api/runs?token=YOUR_APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{ "search": "google maps", "sortBy": "popularity", "maxItems": 100 }'

Endpoint reference: the Apify API docs.

Rank a category in Python

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")

run = client.actor("johnvc/store-actor-intelligence-api").call(
    run_input={"search": "google maps", "sortBy": "popularity", "maxItems": 100}
)

for actor in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(actor["name"], actor.get("monthlyUsers"), actor.get("successRate30Days"), actor.get("pricingModel"))

Two lines of pandas later you have a league table.

Find the best scraper for any site

The Actor ships with ready-made "best scrapers" tasks per category, each returning the ranked field with usage and reliability attached: best Google Maps scrapers, best Amazon scrapers, best LinkedIn scrapers, and best YouTube scrapers, with dozens more on the Actor's examples tab.

Shortlist Actors by audience

Role-based variants do the same for a persona instead of a site: best Actors for developers, for marketers, for recruiters, and for ecommerce sellers.

Let Claude compare scrapers over MCP

Through the Model Context Protocol, Claude, Claude Code, and Cursor can call the Actor as a tool, so "which Instagram scraper has the best 30-day success rate under a cent per result" becomes a grounded, current answer. More on Claude at claude.ai.

FAQ about scraping the Apify Store

Why use a scraper when Apify has an official API?

The official API is built for running Actors, not for market analysis of the store. This scraper flattens the public commercial signals, usage trends, run outcomes, pricing detail, into one row per Actor, which is the shape competitive questions need.

What does the Apify Store scraper cost?

You pay per Actor returned on pay-per-event billing, no subscription and no upstream key, and the per-result price is set to make even a full-store sweep cheap. The live rate is on the Store card, and maxItems caps any run.

How do I pick a reliable scraper from the output?

Sort on successRate30Days first, then sanity-check monthlyUsers and lastRunStartedAt. A tool with high success, active users, and a recent run is maintained; a pretty README with a 60 percent success rate is a warning.

Can Claude run this Store scraper through MCP?

Yes. Expose it via the Apify MCP server and it becomes a callable tool in Claude, Claude Code, Cursor, or any MCP client, useful for agent workflows that need to choose tools with evidence.

Can I schedule the scraper to track a niche weekly?

That is the intended pattern for competitor tracking: save your filter as a task, attach an Apify schedule, and diff usage and pricing across runs. Start from the Apify Store API.

What does the scraper leave out?

Anything not on public listings: private Actors, unpublished drafts, and internal revenue numbers do not exist in the output. Public stats are the whole universe, which is plenty for ranking but not a P&L.

More from Truffle Pig Data

The same sweep works on other catalogs: the RapidAPI Marketplace API does it for API listings, Apple App Store Search for mobile apps, and the G2 Reviews API adds buyer sentiment for the software behind the listings.

Wrapping up

The store is a market, and markets reward whoever has the data. Sweep it once with the Apify Store API and see your category with the numbers attached.